The measurement and analysis of vibrational and/or acoustic data is a widely used technique for determining the type or operating state of a machine. It is generally known that each type of machinery generates a plurality of frequencies dependent upon the operating condition of the machinery. For example, whether the machinery is idling, revving up or revving down changes the frequencies generated by the machinery. The changes in the frequency result from the interaction of the forces required to transition from one machine state to another. Importantly, these frequency shifts reflect changes in the characteristics of the machinery. The complex composite wave formed is unique for each type of machinery and is utilized for identification and recognition.
As illustrated in the prior art, the analysis of the acoustic data can be implemented in the time or frequency domain. In the frequency domain, the frequency spectrum of the machinery is termed an acoustic signature. By comparing the acoustic signature of the unknown or test machinery against a databank of collected acoustic signatures, it is possible to determine the state and/or type of machinery. In certain applications, it is important to determine both the type and state of the machinery. For example, in the telecommunications field thousands of telephone calls are carried over fiber optical cables which are buried underground. The owners can mitigate the consequences of any damage imposed by the machinery on the fiber optic cables by identifying the type and state of any machinery located near the fiber optic cables.
A drawback of the prior art devices is that they require human interaction to render a decision. Accordingly, there is a need to provide an acoustic signature identification and recognition system that alerts the owner by analyzing sound vibrations that impinge upon their equipment and by identifying the encroaching machinery.